Download Files Using Telegram
Description
The following analytic will identify a suspicious download by the Telegram application on a Windows system. This behavior was identified on a honeypot where the adversary gained access, installed Telegram and followed through with downloading different network scanners (port, bruteforcer, masscan) to the system and later used to mapped the whole network and further move laterally.
- Type: TTP
-
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2021-05-06
- Author: Teoderick Contreras, Splunk
- ID: 58194e28-ae5e-11eb-8912-acde48001122
Annotations
Kill Chain Phase
- Command and Control
NIST
- DE.CM
CIS20
- CIS 10
CVE
Search
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`sysmon` EventCode= 15 process_name = "telegram.exe" TargetFilename = "*:Zone.Identifier"
|stats count min(_time) as firstTime max(_time) as lastTime by Computer EventCode Image process_id TargetFilename Hash
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `download_files_using_telegram_filter`
Macros
The SPL above uses the following Macros:
download_files_using_telegram_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Required fields
List of fields required to use this analytic.
- _time
- Computer
- EventCode
- Image
- process_id
- TargetFilename
- Hash
How To Implement
To successfully implement this search, you need to be ingesting logs with the process name and TargetFilename from your endpoints or Events that monitor filestream events which is happened when process download something. (EventCode 15) If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA.
Known False Positives
normal download of file in telegram app. (if it was a common app in network)
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
49.0 | 70 | 70 | Suspicious files were downloaded with the Telegram application on $dest$ by $user$. |
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
Reference
Test Dataset
Replay any dataset to Splunk Enterprise by using our replay.py
tool or the UI.
Alternatively you can replay a dataset into a Splunk Attack Range
source | version: 1